Abstract
The cluster analysis problem is formulated as a problem of global minimization of a function represented as a difference of two convex functions over the unit simplex. The version of branch and bound method for the solution of this problem is studied. Computational testing of suggested algorithm was carried out on Wisconsin Diagnostic Breast Cancer database. We present the results of numerical experiments and discuss them.
This research was supported by the Australian Research Counsil under grant No. A49906152. It has been completed when first author visited School of Information Technology and Mathematical Sciences, University of Ballarat, Australia.
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Thy, H., Bagirov, A.M., Rubinov, A.M. (2001). Clustering via D. C. Optimization. In: Hadjisavvas, N., Pardalos, P.M. (eds) Advances in Convex Analysis and Global Optimization. Nonconvex Optimization and Its Applications, vol 54. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0279-7_11
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DOI: https://doi.org/10.1007/978-1-4613-0279-7_11
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